A Hybrid Artificial Bee Colony Algorithm with Simulated Annealing for Enhanced Community Detection in Social Networks

Narimene Dakiche, K. Benatchba, F. B. Tayeb, Y. Slimani, Mehdi Anis Brahmi
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引用次数: 2

Abstract

In this paper, we propose a hybrid Artificial Bee Colony algorithm with Simulated Annealing (ABC-SA) to address the community detection problem. SA enhances the exploitation by searching the most promising regions located by ABC algorithm. Besides, in order to accommodate the characteristics of social networks, we use locus-based adjacency encoding scheme, in which communities are identified as a graph connected components and Pearson's correlation as structural information to guide the solutions' construction. Results obtained on synthetic and real-word networks show that the proposed algorithm can discover communities more successfully in comparison with traditional ABC algorithm and other state-of-the-art algorithms.
基于模拟退火的混合人工蜂群算法增强社交网络中的社区检测
本文提出了一种模拟退火混合人工蜂群算法(ABC-SA)来解决群体检测问题。SA通过搜索ABC算法定位的最有希望的区域来提高开发效率。此外,为了适应社会网络的特点,我们采用了基于位点的邻接编码方案,该方案将社区识别为图连接组件,并将Pearson关联作为结构信息来指导解决方案的构建。在合成网络和真实世界网络上的实验结果表明,与传统的ABC算法和其他最新算法相比,该算法可以更成功地发现社区。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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